Attention is All You Need

This paper introduces the Transformer, a novel neural network architecture based solely on attention mechanisms, dispensing with recurrence and convolutions entirely. It demonstrates that attention mechanisms alone can achieve state-of-the-art results in machine translation tasks, outperforming traditional recurrent and convolutional models while being more parallelizable and requiring less training time. The Transformer architecture has since become a foundational component in many natural language processing models, including those used for video understanding and clip generation.